I am curious why one would want risk ratios. Unlike odds ratios, they are not interpretable without reference to the base risk. For example a risk ratio of 2 cannot possibly apply to anyone with a starting risk exceeding 1/2.
I think it is most helpful to use one of the existing nomograms to show someone how the base risk and odds ratio translate to final risk, for a range of base risk. Frank David Winsemius wrote > On Jan 30, 2013, at 5:49 AM, aminreza Aamini wrote: > >> Hi all, >> I am very grateful to all those who write to me >> 1) how i can obtain relative risk (risk ratio) in logistic >> regression in R. >> 2) how to obtain the predicted risk for a certain individual using >> fitted regression model in R. > > You obtain the predicted probabilities with something like: > > predict(model, data.frame(x1="a", x2=30), type = "response") > > See ?predict.glm > > This would give the odds ratios (similar but larger than the risk > ratios): > > exp(coef(model)) > > -- > David Winsemius, MD > Alameda, CA, USA > > ______________________________________________ > R-help@ > mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Relative-Risk-in-logistic-regression-tp4657040p4657163.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.